Dr. Wolfgang Fuhl

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University of Tübingen
Dpt. of Computer Science
Human-Computer Interaction
Sand 14
72076 Tübingen
Germany

Telephone
+49 - (0) 70 71 - 29 - 70492
Telefax
+49 - (0) 70 71 - 29 - 50 62
E-Mail
wolfgang.fuhl@uni-tuebingen.de
Office
Sand 14, C206
Office hours
on appointment

Publications

RemoteEye: An open-source high-speed remote eye tracker

mar, 2020

by Benedikt Hosp, Shahram Eivazi, Maximilian Maurer, Woflgang Fuhl, David Geisler, and Enkelejda Kasneci

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Training Decision Trees as Replacement for Convolution Layers

feb, 2020

by W. Fuhl, G. Kasneci, W. Rosenstiel, and E. Kasneci

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Tiny convolution, decision tree, and binary neuronal networks for robust and real time pupil outline estimation

jan, 2020

by W. Fuhl, H. Gao, and E. Kasneci

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Neural networks for optical vector and eye ball parameter estimation

jan, 2020

by W. Fuhl, H. Gao, and E. Kasneci

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A Novel Camera-Free Eye Tracking Sensor for Augmented Reality based on Laser Scanning

jul, 2020

by Johannes Meyer, Thomas Schlebusch, Wolfgang Fuhl, and Enkelejda Kasneci

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Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction

2020

by Wolfgang Fuhl, Yao Rong, and Kasneci Enkelejda

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Explainable Online Validation of Machine Learning Models for Practical Applications

aug, 2020

by Wolfgang Fuhl and Enkelejda Kasneci

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Multi Layer Neural Networks as Replacement for Pooling Operations

aug, 2020

by Wolfgang Fuhl, Yao Rong, Thomas Motz, Michael Scheidt, Andreas Hartel, Andreas Koch, and Enkelejda Kasneci

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Reinforcement learning for the privacy preservation and manipulation of eye tracking data

aug, 2020

by Wolfgang Fuhl, Efe Bozkir, and Enkelejda Kasneci

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Weight and Gradient Centralization in Deep Neural Networks

aug, 2020

by Wolfgang Fuhl and Enkelejda Kasneci

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Rotated Ring, Radial and Depth Wise Separable Radial Convolutions

aug, 2020

by Wolfgang Fuhl and Enkelejda Kasneci

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From perception to action using supervised learning based on observations

aug, 2020

by Wolfgang Fuhl

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Encodji: Encoding Gaze Data Into Emoji Space for an Amusing Scanpath Classification Approach ;)

2019

by Wolfgang Fuhl, Efe Bozkir, Benedikt Hosp, Nora Castner, David Geisler, Thiago C., and Enkelejda Kasneci

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Ferns for area of interest free scanpath classification

jun, 2019

by W. Fuhl, N. Castner, T. C. Kübler, A. Lotz, W. Rosenstiel, and E. Kasneci

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Image-based extraction of eye features for robust eye tracking

apr, 2019

by W. Fuhl

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500,000 images closer to eyelid and pupil segmentation

nov, 2019

by W. Fuhl, W. Rosenstiel, and E. Kasneci

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RemoteEye: An Open Source remote Eye Tracker

dec, 2019

by B. Hosp, S. Evazi, M. Maurer, W. Fuhl, and E. Kasneci

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The applicability of Cycle GANs for pupil and eyelid segmentation, data generation and image refinement

nov, 2019

by W. Fuhl, D. Geisler, W. Rosenstiel, and E. Kasneci

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Learning to validate the quality of detected landmarks

nov, 2019

by W. Fuhl and E. Kasneci

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PuRe: Robust Pupil Detection for Real-Time Pervasive Eye Tracking

may, 2018

by T. Santini, W. Fuhl, and E. Kasneci

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PuReST: Robust Pupil Tracking for Real-Time Pervasive Eye Tracking

jun, 2018

by T. Santini, W. Fuhl, and E. Kasneci

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CBF:Circular binary features for robust and real-time pupil center detection

jun, 2018

by W. Fuhl, D. Geisler, T. Santini, T. Appel, W. Rosenstiel, and E. Kasneci

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Automatic generation of saliency-based areas of interest

sep, 2018

by W. Fuhl, T. Kübler, T. Santini, and E. Kasneci

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Region of interest generation algorithms for eye tracking data

jun, 2018

by W. Fuhl, T. C. Kübler, H. Brinkmann, R. Rosenberg, W. Rosenstiel, and E. Kasneci

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MAM: Transfer learning for fully automatic video annotation and specialized detector creation

2018

by W. Fuhl, N. Castner, L. Zhuang, M. Holzer, W. Rosenstiel, and E. Kasneci

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Eye movement velocity and gaze data generator for evaluation, robustness testing and assess of eye tracking software and visualization tools

2018

by W. Fuhl and E. Kasneci

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BORE: Boosted-oriented edge optimization for robust, real time remote pupil center detection

2018

by W. Fuhl, S. Eivazi, B. Hosp, A. Eivazi, W. Rosenstiel, and E. Kasneci

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Rule based learning for eye movement type detection

2018

by W. Fuhl, N. Castner, and E. Kasneci

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Histogram of oriented velocities for eye movement detection

2018

by W. Fuhl, N. Castner, and E. Kasneci

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Eye movement simulation and detector creation to reduce laborious parameter adjustments

2018

by W. Fuhl, T. Santini, T. Kuebler, N. Castner, W. Rosenstiel, and E. Kasneci

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Saliency Sandbox: Bottom-Up Saliency Framework

feb, 2017

by D. Geisler, W. Fuhl, T. Santini, and E. Kasneci

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EyeRecToo: Open-Source Software for Real-Time Pervasive Head-Mounted Eye-Tracking

feb, 2017

by T. Santini, W. Fuhl, D. Geisler, and E. Kasneci

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EyeLad: Remote Eye Tracking Image Labeling Tool

feb, 2017

by W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, and E. Kasneci

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Fast and Robust Eyelid Outline and Aperture Detection in Real-World Scenarios

mar, 2017

by W. Fuhl, T. Santini, and E. Kasneci

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Ways of improving the precision of eye tracking data: Controlling the influence of dirt and dust on pupil detection

may, 2017

by W. Fuhl, T. C. Kübler, D. Hospach, O. Bringmann, W. Rosenstiel, and E. Kasneci

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CalibMe: Fast and Unsupervised Eye Tracker Calibration for Gaze-Based Pervasive Human-Computer Interaction

may, 2017

by T. Santini, W. Fuhl, and E. Kasneci

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Towards Intelligent Surgical Microscopes: Surgeons Gaze and Instrument Tracking

mar, 2017

by Shahram Eivazi, Wolfgang Fuhl, and Enkelejda Kasneci

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Towards automatic skill evaluation in microsurgery

mar, 2017

by Shahram Eivazi, Michael Slupina, Wolfgang Fuhl, Hoorieh Afkari, Ahmad Hafez, and Enkelejda Kasneci

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PupilNet v2.0: Convolutional Neural Networks for Robust Pupil Detection

2017

by W. Fuhl, T. Santini, G. Kasneci, and E. Kasneci

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Fast camera focus estimation for gaze-based focus control

2017

by W. Fuhl, T. Santini, and E. Kasneci

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Optimal eye movement strategies: a comparison of neurosurgeons gaze patterns when using a surgical microscope

2017

by S. Eivazi, A. Hafez, W. Fuhl, H. Afkari, E. Kasneci, M. Lehecka, and R. Bednarik

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EyeRec: An Open-source Data Acquisition Software for Head-mounted Eye-tracking

feb, 2016

by T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci

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ElSe: Ellipse Selection for Robust Pupil Detection in Real-World Environments

mar, 2016

by W. Fuhl, T. Santini, T. C. Kübler, and E. Kasneci

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Bayesian Identification of Fixations, Saccades, and Smooth Pursuits

mar, 2016

by T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci

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Pupil detection for head-mounted eye tracking in the wild: An evaluation of the state of the art

jun, 2016

by Wolfgang Fuhl, Marc Tonsen, Andreas Bulling, and Enkelejda Kasneci

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Eyes Wide Open? Eyelid Location and Eye Aperture Estimation for Pervasive Eye Tracking in Real-World Scenarios

sep, 2016

by W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, W. Rosenstiel, and E. Kasneci

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Novel methods for analysis and visualization of saccade trajectories

oct, 2016

by T. C. Kübler, W. Fuhl, R. Rosenberg, W. Rosenstiel, and E. Kasneci

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Non-Intrusive Practitioner Pupil Detection for Unmodified Microscope Oculars

dec, 2016

by W. Fuhl, T. Santini, C. Reichert, D. Claus, A. Herkommer, H. Bahmani, K. Rifai, S. Wahl, and E. Kasneci

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Evaluation of State-of-the-Art Pupil Detection Algorithms on Remote Eye Images

sep, 2016

by W. Fuhl, D. Geisler, T. Santini, and E. Kasneci

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Feature-based attentional influences on the accommodation response

2016

by H. Bahmani, W. Fuhl, E. Gutierrez, G. Kasneci, E. Kasneci, and S. Wahl

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PupilNet: Convolutional Neural Networks for Robust Pupil Detection

2016

by W. Fuhl, T. Santini, G. Kasneci, and E. Kasneci

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Analysis of eye movements with Eyetrace

2015

by T. C. Kübler, K. Sippel, W. Fuhl, G. Schievelbein, J. Aufreiter, R. Rosenberg, W. Rosenstiel, and E. Kasneci

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Eyetrace2014: Eyetracking Data Analysis Tool

jan, 2015

by K. Sippel, T. C. Kübler, W. Fuhl, G. Schievelbein, R. Rosenberg, and W. Rosenstiel

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Exploiting the potential of eye movements analysis in the driving context

mar, 2015

by E. Kasneci, T. C. Kübler, C. Braunagel, W. Fuhl, W. Stolzmann, and W. Rosenstiel

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ExCuSe: Robust Pupil Detection in Real-World Scenarios

sep, 2015

by W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci

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Arbitrarily shaped areas of interest based on gaze density gradient

aug, 2015

by W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci

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Research

Eye labeling tool

Ground truth data is an important prerequisite for the development and evaluation of many algorithms in the area of computer vision, especially when these are based on convolutional neural networks or other machine learning approaches that unfold their power mostly by supervised learning. This learning relies on ground truth data, which is laborious, tedious, and error prone for humans to generate. In this paper, we contribute a labeling tool (EyeLad) specifically designed for remote eye-tracking data to enable researchers to leverage machine learning based approaches in this field, which is of great interest for the automotive, medical, and human-computer interaction applications. The tool is multi platform and supports a variety of state-of-theart detection and tracking algorithms, including eye detection, pupil detection, and eyelid coarse positioning.

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Eye Movements Identification

In this paper, we use fully convolutional neural networks for the semantic segmentation of eye tracking data. We also use these networks for reconstruction, and in conjunction with a variational auto-encoder to generate eye movement data. The first improvement of our approach is that no input window is necessary, due to the use of fully convolutional networks and therefore any input size can be processed directly. The second improvement is that the used and generated data is raw eye tracking data (position X, Y and time) without preprocessing. This is achieved by pre-initializing the filters in the first layer and by building the input tensor along the z axis. We evaluated our approach on three publicly available datasets and compare the results to the state of the art.

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Eyetrace

Eyetrace is a tool for analysis of eye-tracking data. It has the approach to bunch a variety of different evaluation methods for a large share of eye trackers supporting scientific work and medical diagnosis. To allow EyeTrace to be compatible to different eye trackers, an additional tool called Eyetrace Butler is used. The Eyetrace Butler performs a data preprocessing and conversion for analysis with Eyetrace. It provides plugins for different eye trackers and converts their data into a format that can be imported and used by Eyetrace.

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Intelligent Surgical Microscope

Head-mounted eye tracking offers remarkable opportunities for research and applications regarding pervasive health monitoring, mental state inference, and human computer interaction in dynamic scenarios. Although a plethora of software for the acquisition of eye-tracking data exists, they often exhibit critical issues when pervasive eye tracking is considered, e.g., closed source, costly eye tracker hardware dependencies, and requiring a human supervisor for calibration. In this paper, we introduce EyeRecToo, an open-source software for real-time pervasive head-mounted eye-tracking. Out of the box, EyeRecToo offers multiple real-time state-of-the-art pupil detection and gaze estimation methods, which can be easily replaced by user implemented algorithms if desired. A novel calibration method that allows users to calibrate the system without the assistance of a human supervisor is also integrated. Moreover, this software supports multiple head-mounted eye-tracking hardware, records eye and scene videos, and stores pupil and gaze information, which are also available as a real-time stream. Thus, EyeRecToo serves as a framework to quickly enable pervasive eye-tracking research and applications.

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Robust Pupil Detection and Gaze Estimation

The reliable estimation of the pupil position in eye images is perhaps the most important prerequisite in gaze-based HMI applications. While there are many approaches that enable accurate pupil tracking under laboratory conditions, tracking the pupil in real-world images is highly challenging due to changes in illumination, reflections on glasses or on the eyeball, off-axis camera position, contact lenses, and many more.

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Teaching

Course Term
Advanced Topics in Perception Engineering
Programmieren mobiler eingebetteter Systeme
Programmieren mobiler eingebetteter Systeme
Programmieren mobiler eingebetteter Systeme
Programmieren mobiler eingebetteter Systeme
Technische Anwendungen der Informatik: Hard- und Software aktueller Eye-Tracking-Systeme
Technische Anwendungen der Informatik: Hard- und Software aktueller Eye-Tracking-Systeme
Seminar: Advanced Topics in Perception Engineering

Finished Thesis Topics

10.07.2019

Vein extraction and eye rotation determination

The first step is setting up an recording environment with fixed subject position. This environment is used for data acquisition with predefined head rotations of the subjects. Based on this data an algorithm has to be developed measuring the eyeball rotation of the subject. The resulting angle is then compared and validated based on the head rotation.

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10.07.2019

EyeTrace CUDA extesion

EyeTrace is a software for gaze data visualization and analysis. Due to the increasing amount of data these visualizations need more computation time. In this thesis existing visualizations should be implemented using CUDA for GPU computations. Additionally this includes a data storage model making it possible to shift the data between the GPU and the host computer. Due to the fact that nowadays not all computers have a CUDA capable card the modul should also allow CPU computations. This should be determined automatically by the module.

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10.07.2019

3D Eyeball generation based on vein motion

The first step is robust feature extraction. This can be done using SURF, SIFT, BRISK or MSER features if sufficient. Those features have to be mapped on features found in consecutive images. Based on the displacement a 3D model has to be computed. This model is used afterwards for gaze position estimation.

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News

24.06.2020

Paper accepted at the International Conference on Pattern Recognition 2020 (ICPR)

The paper “Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction” was accepted at the International Conference on Pattern Recognition 2020.

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24.03.2020

RemoteEye published in Behavior Research Methods

Recent Publication in the journal Behavior Research Methods (March 2020)

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19.03.2020

Eight papers accepted at 2020 Eye Tracking and Reseach Applications Conference

The Human - Computer Interaction group (formerly Perception Engineering) are represented with 8 papers at the 2020 Eye Tracking and Reseach Applications Conference (ETRA).

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